AI news ·
Prosper AI and Uncovr raise funding as Mass General Brigham launches clinical AI benchmark
Healthcare AI sees $30M for admin tasks, a clinical language benchmark, and $7M for surgical video analysis. Investments target real-world clinical and operational tools.
Three recent healthcare AI developments-a $30 million funding round for an administration platform, a new benchmark for evaluating clinical language models, and seed funding for a surgical AI startup-signal continued investment in tools designed to handle real-world clinical and operational tasks.
Prosper AI secures $30M to automate administrative workflows
Prosper AI closed a $30 million Series A round led by Andreessen Horowitz. Base10, Emergence Capital, Y Combinator and Company Ventures participated. The company's platform handles patient calls, insurance verification, appointment scheduling and billing for healthcare providers. The funding will go toward team growth, deeper electronic health record integration and market expansion, according to a news release.
Mass General Brigham releases multilingual clinical AI benchmark
Researchers at Mass General Brigham introduced Bridge, a benchmark that tests how well large language models interpret clinical text. Unlike tools that rely on standardized exam questions, Bridge draws from electronic health records, clinical case reports and multilingual doctor-patient conversations. The design reflects the complexity of real patient care, the health system said.
Uncovr raises $7M to analyze surgical video
Uncovr, a surgical AI company founded in 2025, raised $7 million in seed funding. Index Ventures led the round, with participation from Seedcamp, No Labels Ventures, Entrepreneurs First, Frst, and angel investors including Othman Laraki and Charlie Songhurst. Uncovr's platform generates operative reports and procedural codes from surgical video. The money will be used to expand the engineering team, a spokesperson said.
Why this matters for healthcare professionals
These three moves show that AI investment is targeting the messy, unstructured data that clinicians and administrators handle daily. For anyone responsible for clinical documentation, scheduling, or revenue cycle work, tools that automate insurance verification, generate operative notes, or accurately read multilingual records could reduce administrative burden and free up time for patient care. Tracking developments like these helps teams evaluate which AI for Healthcare capabilities are maturing from pilot projects into funded products with institutional backing.